zvelo is the provider of the most advanced URL Database for Web Categorization and Malicious Detection—designed for OEMs, device manufacturer’s, and Network Security vendors. zvelo’s content categorization engines power web filtering and parental controls, whitelists and blacklists for anti-virus companies, home network protection devices, and much more. By categorizing content into topic-based, objectionable, and malicious category groupings—zveloDB provides the most advanced malicious detection for advanced threat intelligence and cybersecurity.
We’re excited to announce our latest malicious detection data service, PhishBlocklist™. Powered by our newly launched “Angler” Phishing Detection System, PhishBlocklist is designed to provide the industry’s most advanced and effective source for active and emerging phishing URLs—including zero-hour threats that APWG, Phishtank, and other services haven’t detected.
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In this blog, we identify the five critical infrastructure requirements cybersecurity solutions MUST achieve maximum user protection from malicious threats.
We often get asked how we are able to attain such high levels of coverage with our URL database. Here, we explain our approach as well as how we got there.
In this blog, we explore the most common DNS filtering misconceptions, provide clarification, and identify what separates premium solutions from the pack.
HTF’s market study provides a comprehensive overview of the growing Web Filtering Service Market and projects “Phenomenal Growth” in coming years. zvelo is proud to power many of the web filtering market leaders. Helping build a safer internet for all with unmatched ActiveWeb coverage and accuracy.
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This blog explores considerations and criteria for evaluating a URL database or classification technology partner that shares your commitment to success. We’ve outlined the important considerations and criteria for performing an evaluation of web filtering technologies. Protection, coverage, and accuracy are most important—but we’ll also show you how to prepare test URLs so that you can confidently compare multiple solutions and save time.
The purpose of this article is to provide a quick and easy visual reference the web filtering market segments and to identify where various services are positioned in the market and on the value curve.
In this blog, we explore the category updates that require real-time protection as well as how we deliver instant updates to URL databases worldwide.
One of the key factors for categorizing web content is, of course, understanding the target language of the content. By leveraging language translation, and applying machine learning and other techniques for categorization, we are able to achieve a high level of accuracy and consistency
Continuing with our series on bias, in this blog, we explore editorial bias and the challenges it presents in accurately categorizing forms of web content.